Various classes of block diagrams describe computations that can be performed on application specific computational hardware, such as a computer, microcontroller, FPGA, and custom hardware. Classes of such block diagrams include time-based block diagrams, such as those found within Simulink®, from The MathWorks, Inc. of Natick, Mass., state-based and flow diagrams, such as those found within Stateflow®, from The MathWorks, Inc. of Natick, Massachusetts, data-flow diagrams, and software diagrams, such as those found in the Unified Modeling Language.
Historically, engineers and scientists have utilized time-based block diagram models in numerous scientific areas such as Feedback Control Theory and Signal Processing to study, design, debug, and refine dynamic systems. Dynamic systems, which are characterized by the fact that their behaviors change over time, are representative of many real-world systems. Time-based block diagram modeling has become particularly attractive over the last few years with the advent of software packages, such as Simulink®. Such packages provide sophisticated software platforms with a rich suite of support tools that makes the analysis and design of dynamic systems efficient, methodical, and cost-effective.
A dynamic system (either natural or man-made) is a system whose response at any given time is a function of its input stimuli, its current state, and the current time. Such systems range from simple to highly complex systems. Physical dynamic systems include a falling body, the rotation of the earth, bio-mechanical systems (muscles, joints, etc.), bio-chemical systems (gene expression, protein pathways), weather and climate pattern systems, etc. Examples of man-made or engineered dynamic systems include: a bouncing ball, a spring with a mass tied on an end, automobiles, airplanes, control systems in major appliances, communication networks, audio signal processing, nuclear reactors, a stock market, etc. Professionals from diverse areas such as engineering, science, education, and economics build mathematical models of dynamic systems in order to better understand system behavior as it changes with the progression of time. The mathematical models aid in building “better” systems, where “better” may be defined in terms of a variety of performance measures such as quality, time-to-market, cost, speed, size, power consumption, robustness, etc. The mathematical models also aid in analyzing, debugging and repairing existing systems (be it the human body or the anti-lock braking system in a car). The models may also serve an educational purpose of educating others on the basic principles governing physical systems. The models and results are often used as a scientific communication medium between humans. The term “model-based design” is used to refer to the use of block diagram models in the development, analysis, and validation of dynamic systems.
In designing models of modern systems, the size of the models is being increased to a stunning level of complexity. Hundreds of thousands of components may be included in the models. In order to manage the complexity of the models, the technologies of hierarchy, abstraction, and partitioning are utilized. The hierarchy is typically captured by so-called ‘subsystems.’ Because subsystems may contain their own subsystems, they provide a mechanism for the hierarchical structure of the models. Abstraction allows dismissing system behavior in the models if it is not important to the problem that needs to be addressed and for which the models are designed. Including arbitrary detail often complicates and hampers the design, analysis, and/or synthesis of the model. Partitioning is used to create separate and independent modules (or ‘units’) in the models. The partitioning facilitates engineers to work on engineering projects where each engineer (or a group of engineers) is responsible for one unit of the models. The aforementioned technologies may help design models that have a high level of complexity.